Main
Rafael Uchoa de Lima
Education
Post-graduation in Data Science and Decision
Insper
São Paulo, Brazil
2022 - 2021
Bachelor of Science in Computer Science
University of Maryland
College Park, Maryland, USA
2019 - 2014
- Design Cultures & Creativity Honors Program
Professional Experience
Data Scientist
MindMiners
São Paulo, Brazil
Current - 2019
- Built interactive dashboards for visualization of data collected by client-made surveys, using Dash, Plotly and Pandas;
- Analyzed app usage metrics and the company’s internal performance data, using SQL and R;
- Created Machine Learning models for text classification and sentiment analysis;
Volunteer Teaching Assistant
Girls Who Code - University of Maryland
College Park, Maryland, USA
2019 - 2018
- Taught high school and middle school girls the fundamentals of programming, using Python;
Relevant Coursework
Data Science: Análise Exploratória de Dados
Insper
São Paulo, Brazil
2020 - 2020
- Studied a framework of data exploration involving analysis, transformation and visualization
- Analyzed and extracted patterns from real world data, contributing to a more efficient decision-making process;
- Created dashboard to present data analysis reports, using data visualization tools;
Data Structures
University of Maryland
College Park, Maryland, USA
2018 - 2018
- Implemented efficient, 1-dimensional data structures, including AVL Trees, Hash Tables and Suffix Arrays;
- Implemented multi-dimensional data structures, including KD-Trees and Quad-Trees;
- Studied the LZW Algorithm for lossless data compression;
Design and Analysis of Computer Algorithms
University of Maryland
College Park, Maryland, USA
2017 - 2017
- Implemented graph and greedy algorithms, including algorithms for bipartiteness, topological sorting, scheduling and minimal spanning trees;
- Studied dynamic programming for problems such as sequence alignment and shortest paths;
- Studied randomized algorithms such as minimum cut and game tree evaluation;
Introduction to Machine Learning
University of Maryland
College Park, Maryland, USA
2017 - 2017
- Implemented different approaches to Machine Learning, including Linear Separators and Neural Networks;
- Studied Principal Component Analysis and probabilistic models, including the Bernoulli Model and Logistic Regression;
- Studied Machine Learning theory, including computational learning theory and PAC efficiency;
Disclaimer
Made with the R packages pagedown and datadrivencv.
Source code available on GitHub.
Last updated on 2022-11-09.